Collection and Deduction of Income Tax at Source (Withholding Agents Perspective) (Taxpayer’s Facilitation Guide) Brochure – IR-IT-04 July 2011 Revenue Division Federal Board of Revenue Government of Pakistan helpline@fbr.gov.pk 0800-00-227‚ 051-111-227-227 www.fbr.gov.pk Our Vision To be a modern‚ progressive‚ effective‚ autonomous and credible organization for optimizing revenue by providing quality service and promoting compliance with tax and related laws Our Mission
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1 CIPD unit 4DEP - Version 2 18.03.10 Unit title Developing Yourself as an Effective Human Resources or Learning and Development Practitioner Level 4 1 Credit value 4 Unit code 4DEP Unit review date Sept. 2011 Purpose and aim of unit The CIPD has developed a map of the HR profession (HRPM) that describes the knowledge‚ skills and behaviours required by human resources (HR) and learning and development (L&D) professionals. This unit is designed to enable the learner
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Treatment Process in Houston CIVT 301 Outline Wastewater collection data in Houston What is sewage treatment? Where does wastewater come from? Factors that affect the flow of pipelines Industrial wastewater? Storm water/ Data The treatment plant operator Sources of wastewater Why treat wastes Waste water treatment facilities Treatment processes Drinking water What can be done to help? Wastewater collection data in Houston 640 square miles area 3 million citizens served 6
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Department of Education Office of Federal Student Aid Data Migration Roadmap: A Best Practice Summary Version 1.0 Final Draft April 2007 Data Migration Roadmap Table of Contents Table of Contents Executive Summary ................................................................................................................ 1 1.0 Introduction ......................................................................................................................... 3 1.1 1.2 1.3 1.4 Background
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University CS 450 Data Mining‚ Fall 2014 Take-Home Test N#1 Date: September 22nd‚ 2014 Final deadline for submission September 29th‚ 2014 Weighting: 5% Total number of points: 100 Instructions: 1. Attempt all questions. 2. This is an individual test. No collaboration is permitted for assessment items. All submitted materials must be a result of your own work. Part I Question 1 [20 points] Discuss whether or not each of the following activities is a data mining task.
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Ensuring Data Storage Security in Cloud Computing Cong Wang‚ Qian Wang‚ and Kui Ren Department of ECE Illinois Institute of Technology Email: {cwang‚ qwang‚ kren}@ece.iit.edu Wenjing Lou Department of ECE Worcester Polytechnic Institute Email: wjlou@ece.wpi.edu Abstract—Cloud Computing has been envisioned as the nextgeneration architecture of IT Enterprise. In contrast to traditional solutions‚ where the IT services are under proper physical‚ logical and personnel controls‚ Cloud Computing
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Big Data Management: Possibilities and Challenges The term big data describes the volumes of data generated by an enterprise‚ including Web-browsing trails‚ point-of-sale data‚ ATM records‚ and other customer information generated within an organization (Levine‚ 2013). These data sets can be so large and complex that they become difficult to process using traditional database management tools and data processing applications. Big data creates numerous exciting possibilities for organizations‚
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Enhancing Customer Data Enhanced Customer Data Repository is a secure and fully supported data repository with problem determination tools and functions. It updates problem management records (PMR) and maintains full data life cycle management. · combination of all the internal structured business data (CRM‚ ERP‚ POS and all the internal system data) and external unstructured data ( Social media data‚ feedback surveys‚ Audios‚ Videos‚ streaming data‚ Call center data‚ images) · unmanageable volumes
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measures widely used to measure complexity in manufacturing systems. With reference to this second framework‚ two indexes were selected (static and dynamic complexity index) and a Business Dynamic model was developed. This model was used with empirical data collected in a job shop manufacturing system in order to test the usefulness and validity of the dynamic complex index. The Business Dynamic model analyzed the trend of the index in function of different inputs in a selected work center. The results
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LECTURE 1 DATA TYPES Our interactions (inputs and outputs) of a program are treated in many languages as a stream of bytes. These bytes represent data that can be interpreted as representing values that we understand. Additionally‚ within a program we process this data that can be interpreted as representing values that we understand. Additionally‚ within a program we process this data in various way such as adding them up or sorting them. This data comes in different forms. Examples include: your
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